Porous Microstructure Analysis


Physics-based digital microstructure modeling and AI-driven optimization of porous materials

This research field focuses on physics-based reconstruction, quantitative characterization, and multi-physics analysis of porous microstructures for advanced material and process design. We develop simulation-driven digital twins of pore-scale structures by integrating particle-based modeling, voxelized image analysis, and AI-assisted optimization frameworks.

Research Topics

DEM-based Microstructure Generation

  • Particle packing and calendaring simulation for battery electrodes
  • Controlled bimodal and multimodal particle size distribution (PSD) design
  • Structure–property relationships under compaction processes

Voxelization & Digital Reconstruction

  • Automated voxelization pipelines (DEM → TIFF/VTK workflows)
  • Representative Volume Element (RVE) analysis
  • Porosity, tortuosity, connectivity, and percolation quantification

Effective Property Estimation

  • Effective ionic and electronic conductivity prediction
  • Specific surface area and active transport interface evaluation
  • Bubble point pressure (BPP) and pore-throat characterization
  • Surrogate modeling (Gaussian Process, RSM, Bayesian optimization)

Coupled Multi-Physics in Porous Media

  • Flow and heat transfer simulations in complex pore networks
  • SPH-based multiphase transport modeling
  • Darcy–Forchheimer porous resistance modeling
  • Microstructure-informed macro-scale property upscaling

AI–Computational Mechanics Integration

  • Surrogate-assisted microstructure optimization
  • Multi-objective design under structural constraints
  • High-dimensional design space exploration

Porous microstructure analysis